## region_viticole cepage
## Alsace gewurztraminer 231
## pinot auxerrois 137
## riesling 229
## Bordelais cabernet franc 118
## cabernet sauvignon 522
## merlot 278
## sauvignon blanc 257
## semillon 139
## Bourgogne chardonnay 183
## gamay 117
## meunier 3
## pinot noir 203
## Champagne chardonnay 403
## meunier 354
## pinot noir 6
## Charentes cabernet sauvignon 3
## ugni blanc 287
## Cotes-du-Rhone cinsault 12
## gamay 11
## grenache 23
## muscat de hambourg 22
## muscat petits grains 6
## syrah 26
## Jura poulsard 87
## savagnin 207
## trousseau 213
## Languedoc cabernet franc 8
## cabernet sauvignon 17
## carignan 8
## chardonnay 17
## mourvedre 4
## muscat petits grains 19
## pinot noir 14
## sauvignon blanc 6
## Provence cabernet sauvignon 98
## carignan 21
## cinsault 24
## grenache 34
## mourvedre 22
## muscat de hambourg 36
## syrah 27
## Val de Loire cabernet franc 178
## chenin 319
## melon 275
## sauvignon blanc 285
## dtype: int64
## pourcentage_esca
## count mean std
## region_viticole
## Alsace 597.0 5.659014 5.796469
## Bordelais 1314.0 3.966113 5.312952
## Bourgogne 506.0 3.015018 4.670658
## Champagne 763.0 0.783341 1.016968
## Charentes 290.0 7.322215 6.424814
## Cotes-du-Rhone 100.0 1.930000 3.586449
## Jura 507.0 9.424852 8.850297
## Languedoc 93.0 5.326325 9.302493
## Provence 262.0 4.170483 5.762116
## Val de Loire 1057.0 6.453154 5.976168
## count 5489.000000
## mean 4.776286
## std 6.154520
## min 0.000000
## 25% 0.666667
## 50% 2.483248
## 75% 6.666667
## max 63.333333
## Name: pourcentage_esca, dtype: float64
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=6,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=100,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 6 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 100 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## region rmse mae
## 0 Alsace 3.928968 2.794687
## 1 Bordelais 4.490610 2.825330
## 2 Bourgogne 3.945469 2.404211
## 3 Champagne 1.152085 0.728599
## 4 Charentes 8.204814 6.017232
## 5 Cotes-du-Rhone 5.512553 2.837171
## 6 Jura 6.102994 4.427816
## 7 Languedoc 11.606178 5.073838
## 8 Provence 6.012571 3.526684
## 9 Val de Loire 6.185696 4.360010
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.05, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.05 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 3.0787242981220952
##
## Train mean error:
## 2.256282784979964
##
## Train r²:
## 0.7559271543002186
##
## Test RMSE:
## 5.789010178963023
##
## Test mean error:
## 3.603371055598425
##
## Test r²:
## 0.16419893386793669
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.05, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.05 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 2.786107886604798
##
## Train mean error:
## 1.907100895849971
##
## Train r²:
## 0.7776664141232649
##
## Test RMSE:
## 3.783499915231343
##
## Test mean error:
## 2.4633329924762033
##
## Test r²:
## 0.40421613802953654
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=6,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 6 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 3.0973031211558157
##
## Train mean error:
## 1.7489621122169825
##
## Train r²:
## 0.8761305168095069
##
## Test RMSE:
## 2.986497180684029
##
## Test mean error:
## 2.0043854641345913
##
## Test r²:
## 0.1756280495866092
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=6,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 6 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=100,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 100 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 0.9377091871661601
##
## Train mean error:
## 0.6653347966165406
##
## Train r²:
## 0.2649591641198136
##
## Test RMSE:
## 1.0806526118892725
##
## Test mean error:
## 0.7485246410795099
##
## Test r²:
## 0.009004906854850642
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=100,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 100 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 4.208786091751969
##
## Train mean error:
## 3.2356591253332585
##
## Train r²:
## 0.6874715793415148
##
## Test RMSE:
## 5.175055672311247
##
## Test mean error:
## 4.19543047717014
##
## Test r²:
## 0.27600028608446914
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 1.2738705832904655
##
## Train mean error:
## 0.8710663345952826
##
## Train r²:
## 0.9321605484956036
##
## Test RMSE:
## 2.7642431801188363
##
## Test mean error:
## 1.530050558348497
##
## Test r²:
## 0.34859857054930976
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.05, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.05 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 4.769345475468805
##
## Train mean error:
## 3.470189957225011
##
## Train r²:
## 0.7668068118030442
##
## Test RMSE:
## 6.1486722787250905
##
## Test mean error:
## 4.311950152772929
##
## Test r²:
## 0.3680538507805982
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.05, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.05 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 0.3777447263639509
##
## Train mean error:
## 0.27238823997420886
##
## Train r²:
## 0.9982656624303965
##
## Test RMSE:
## 10.861559162482653
##
## Test mean error:
## 5.368725670661857
##
## Test r²:
## 0.1631265783730237
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 4.415485518203939
##
## Train mean error:
## 2.8600886807297212
##
## Train r²:
## 0.6399318912231008
##
## Test RMSE:
## 3.2303132434780206
##
## Test mean error:
## 2.59528615939542
##
## Test r²:
## 0.3872593632016734
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.01, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=200,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.01 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 200 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | 0 |
##
## Train RMSE:
## 4.88243531346175
##
## Train mean error:
## 3.705909269500348
##
## Train r²:
## 0.4626109856818992
##
## Test RMSE:
## 5.034684531444679
##
## Test mean error:
## 3.74259909414069
##
## Test r²:
## 0.11641425421063563
XGBRegressor(base_score=None, booster=None, callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, device=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, feature_types=None,
feature_weights=None, gamma=None, grow_policy=None,
importance_type=None, interaction_constraints=None,
learning_rate=0.1, max_bin=None, max_cat_threshold=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=3,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, multi_strategy=None, n_estimators=50,
n_jobs=None, num_parallel_tree=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | objective | 'count:poisson' | |
| base_score | None | |
| booster | None | |
| callbacks | None | |
| colsample_bylevel | None | |
| colsample_bynode | None | |
| colsample_bytree | None | |
| device | None | |
| early_stopping_rounds | None | |
| enable_categorical | False | |
| eval_metric | None | |
| feature_types | None | |
| feature_weights | None | |
| gamma | None | |
| grow_policy | None | |
| importance_type | None | |
| interaction_constraints | None | |
| learning_rate | 0.1 | |
| max_bin | None | |
| max_cat_threshold | None | |
| max_cat_to_onehot | None | |
| max_delta_step | None | |
| max_depth | 3 | |
| max_leaves | None | |
| min_child_weight | None | |
| missing | nan | |
| monotone_constraints | None | |
| multi_strategy | None | |
| n_estimators | 50 | |
| n_jobs | None | |
| num_parallel_tree | None | |
| random_state | None | |
| reg_alpha | None | |
| reg_lambda | None | |
| sampling_method | None | |
| scale_pos_weight | None | |
| subsample | None | |
| tree_method | None | |
| validate_parameters | None | |
| verbosity | None | |
| verbose | -1 |
## <IPython.core.display.HTML object>